Yitao Wu

2 accepted papers

2026

Rethinking the Spatio-Temporal Alignment of End-to-End 3D Perception

Xiaoyu Li, Peidong Li, Xian Wu, Long Shi, Dedong Liu, Yitao Wu +4

AAAI 2026technical

Spatio-temporal alignment is crucial for temporal modeling of end-to-end (E2E) perception in autonomous driving (AD), providing valuable structural and textural prior information. Existing methods typically rely on the attention mechanism to align objects across frames, simplifying the motion model

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2024

Fast-Poly: A Fast Polyhedral Algorithm for 3D Multi-Object Tracking

Xiaoyu Li, Dedong Liu, Yitao Wu, Xian Wu, Lijun Zhao, Jinghan Gao

RA-L 2024

3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with accuracy and latency consistency. In this letter, we propose Fast-Poly, a fast and effective filter-based method fo

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